Departments may offer a course known as SPECIAL TOPICS in which a student or a group of students study or read widely in a field of special interest. It is understood that this course will not normally duplicate any other course regularly offered in this curriculum and that the student will work in this course as independently as the instructor thinks possible. A Special Topics course may be elected in any semester. The course should be given a unique name that will be recorded on the student’s transcript.

A special topics course focused on core economic theory. Intended for students who have, in the past, received a D in a core theory course in economics and who therefore need to take a special topics course focused on that area of core theory to satisfy the major requirements.

Fall and spring semesters. The Department.

A study of the analysis of quantitative data, with special emphasis on the application of statistical methods to economic problems. A student may not receive credit for both ECON 360 and ECON 361.

Requisite: MATH 111, or equivalent and at least a "B" grade in ECON 111/111E or a "B-" in ECON 200–290, or equivalent. Fall and spring semesters.

Fall semester: Limited to 40 students. Professor Sims.

Spring semester: Limited to 40 students. Professor Sims and Professor Debnam Guzman.

Departments may offer a course known as SPECIAL TOPICS in which a student or a group of students study or read widely in a field of special interest. It is understood that this course will not normally duplicate any other course regularly offered in this curriculum and that the student will work in this course as independently as the instructor thinks possible. A Special Topics course may be elected in any semester. The course should be given a unique name that will be recorded on the student’s transcript.

Independent reading course.

Fall and spring semesters. The Department.

A fundamental problem in computer science is that of organizing data so that it can be used effectively. This course introduces basic data structures and their applications. Major themes are the importance of abstraction in program design and the separation of specification and implementation. Program correctness and algorithm complexity are also considered. Data structures for lists, stacks, queues, dictionaries, sets, and graphs are discussed. This course will provide advanced programming experience.